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NIPS
2007
13 years 11 months ago
What makes some POMDP problems easy to approximate?
Point-based algorithms have been surprisingly successful in computing approximately optimal solutions for partially observable Markov decision processes (POMDPs) in high dimension...
David Hsu, Wee Sun Lee, Nan Rong
AAAI
2012
12 years 10 days ago
Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Frans Adriaan Oliehoek, Matthijs T. J. Spaan
SUTC
2006
IEEE
14 years 4 months ago
Energy and Communication Efficient Group Key Management Protocol for Hierarchical Sensor Networks
- In this paper, we describe a group key management protocol for hierarchical sensor networks where instead of using pre-deployed keys, each sensor node generates a partial key dyn...
Biswajit Panja, Sanjay Kumar Madria, Bharat K. Bha...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 7 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
RTSS
2009
IEEE
14 years 4 months ago
New Response Time Bounds for Fixed Priority Multiprocessor Scheduling
Recently, there have been several promising techniques developed for schedulability analysis and response time analysis for multiprocessor systems based on over-approximation. Thi...
Nan Guan, Martin Stigge, Wang Yi, Ge Yu